Exploring the use of shape and texture descriptors of positron emission tomography tracer distribution in imaging studies of neurodegenerative disease

Abstract

Positron emission tomography (PET) data related to neurodegeneration are most often quantified using methods based on tracer kinetic modeling. In contrast, here we investigate the ability of geometry and texture-based metrics that are independent of kinetic modeling to convey useful information on disease state. The study was performed using data from Parkinson’s disease subjects imaged with 11C-dihydrotetrabenazine and 11C-raclopride. The pattern of the radiotracer distribution in the striatum was quantified using image-based metrics evaluated over multiple regions of interest that were defined on co-registered PET and MRI images. Regression analysis showed a significant degree of correlation between several investigated metrics and clinical evaluations of the disease ( p < 0.01). The best results were obtained with the first-order moment invariant of the radioactivity concentration values estimated over the full structural extent of the region as defined by MRI ( R2 = 0.94). These results demonstrate that there is clinically relevant quantitative information in the tracer distribution pattern that can be captured using geometric and texture descriptors. Such metrics may provide an alternate and complementary data analysis approach to traditional kinetic modeling.